Data Science In Various Industries
Today, companies apply various solutions to collect data they produce.
However, raw data is of no use. It is necessary to manage, analyze, interpret this data and obtain valuable information from this data. At this point, data science comes into play.
Data science uses data in various industries thanks to personalized solutions. It provides high value-added information by utilizing various techniques in large, medium and small enterprises.
Let’s take a look at the sectors where data science is used the most.
1. Data Science In Banking And Finance
By leveraging big data technologies, banks can efficiently manage their resources, make smarter decisions and improve their performance.
For example, by using machine learning, credit cards, accounting and insurance frauds can be effectively detected and prevented. Proactive fraud detection in banking is required to provide security to customers and employees.
In addition, data science can be used to predict bank customers’ possibilities of responding positively to a promotion or an offer by making use of behavioral, demographic and historical purchasing data. Thus, banks improve their relations with their customers.
2. Data Science In Insurance Sector
The insurance sector is considered one of the most competitive and less predictable business areas. It’s about risk instantly. Today, insurance companies have a broader source of information for risk assessment. Big Data technologies are used to anticipate, monitor and analyze risks and claims to develop effective strategies to attract customers.
Insurance fraud brings huge financial losses to insurance companies every year. Data science platforms and software can detect fraudulent behaviors, suspicious connections, using multiple techniques.
Data science algorithms give insurers the opportunity to dynamically adjust quoted premiums. Price optimization helps increase customer loyalty. However, profit and income are maximized.
All customers’ attitudes, preferences, behaviors or personal informations are determined and divided into groups by data science algorithms. This grouping enables the development of relevant attitudes and solutions, especially for specific customers. As a result, cross-selling policies can be developed and personal services can be tailored for each customer segment.
3. Data Science In Retail Sector
Retailers must accurately predict what their customers want and develop strategies accordingly. If they do not, they will lag behind in competition with their rivals. Data analysis provides retailers with the information they need to keep their customers happy and brought them to their stores.
For example, retailers can use data science to leverage their customers’ shopping experience to enable them to make purchasing decisions by satisfying their customers.
4. Data Science in Medicine Sector
The medical industry makes great use of big data and analytics to improve health in a variety of ways. For example, it enables doctors to obtain important informations from patients by using wearable technologies for better care of patients. Wearable technologies provide informations such as whether the patient is taking his medication and whether he / she has correctly applied the treatment plan. Data collected over time gives physicians comprehensive information about the condition of patients.
Data science helps doctors make a more accurate diagnosis, improve the method of treatment, and facilitates personal medical treatment.
5. Data Science in Tourism
Using big data analysis in customer relations in tourism sector significantly increases your performance and benefits.
Analyzing data such as location, traveler profile, type of tourism, individual or social habits, preferences, and economic indicator enables the campaigns for tourism to be customized as much as possible.
Thanks to the application of mathematical models and predictive algorithms, customers’ behaviors can be estimated and examined. These data studies allow tourism companies to know what to offer their customers, when and at what price.
6. Data Science in Education
Education is no exception in the 21st century where data is available in all areas of life.
Thanks to advances in Big Data analytics, it became possible for teachers to examine student needs.
As a result of monitoring student needs, teachers can give appropriate answers to their students and even change their teaching methods to meet students’ expectations. This provides an equal educational platform to ensure the participation of all students and improve their skills.
Data scientists can apply a variety of predictive analytical techniques to increase teachers motivation for students’ lesson work.
In addition, universities can analyze new skill sets and organize courses using predictive analytical methods.
7. Data Science In Telecom
Real-time data from multiple sources can be used to develop products offered by the telecom industry. Customer needs can be determined by analyzing customer use. Thus, new product packages suitable for customers can be created.
Data science helps collect and analyze customer data, minimizes customer loss. This lowers operating costs and enables better decision making.
Big data solutions help understand the customer better by examining how they use the services. For example, a customer who calls more often to a particular country or watches optional movies can be targeted for a campaign that covers both areas.
Business Intelligence Specialist
